spectra-cli 0.1.1

Generate production-ready DevOps files for your projects using AI

Spectra CLI

🎯 Generate production-ready DevOps files for your projects using AI

Spectra CLI scans your project, identifies the tech stack, and automatically generates production-ready DevOps files including:

• Dockerfile - Multi-stage, optimized Docker images
• docker-compose.yml - Local development setup
• GitHub Actions CI/CD - Automated build and deployment workflows

Features

• 🔍 Smart Project Scanning - Automatically detects your tech stack (Node.js, Python, Java, Go, Rust, PHP, etc.)
• 🤖 AI-Powered Generation - Uses Gemini AI to generate production-ready DevOps files
• ⚡ Lightning Fast - Instant responses for common stacks via template caching (80% of users)
• 🔄 Async Processing - Background job queue for custom stacks with real-time progress
• 🔒 Production-Ready - Follows best practices for security and performance
• 🚀 Zero Configuration - Works out of the box with sensible defaults

Installation

Option 1: Global install (recommended for users)

Install via pipx (isolated global CLI):

# Install pipx if needed
python3 -m pip install --user pipx && python3 -m pipx ensurepath

# Install the Spectra CLI globally (after PyPI publish)
pipx install spectra-cli

# Use from any project
spectra init

If you prefer using pip:

pip install --user spectra-cli
spectra init

Option 2: Install from Source (Development)

# Clone the repository
git clone https://github.com/yourusername/spectra-cli.git
cd spectra-cli

# Create a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Install in editable mode
pip install -e .

Option 3: Install via pip (Production)

pip install spectra-cli

Quick Start

1. Navigate to your project directory:

   cd /path/to/your/project
   

2. Run Spectra:

   spectra init
   

3. That's it! Spectra will:

   • Scan your project
   • Detect your tech stack
   • Generate Dockerfile, docker-compose.yml, and CI/CD workflows

Performance

System Design v2 includes major performance improvements:

• Template Caching: Common stacks (Python, Node.js, Go, Rust, Java) get instant responses (<1 second)
• Async Job Queue: Custom stacks use background processing with real-time polling
• No Timeouts: Architecture solves Vercel timeout issues completely

See API_V2_DOCS.md for detailed architecture documentation.

Configuration

Environment Variables

CLI:

• SPECTRA_API_URL - API endpoint URL (default: https://spectra-cli.vercel.app/)

  export SPECTRA_API_URL='https://your-api.vercel.app/'
  

API Server (Vercel):

• OPENROUTER_API_KEY - OpenRouter API key (get from https://openrouter.ai/keys - free tier available)
• UPSTASH_REDIS_URL - Upstash Redis URL (optional, for production job queue)
• UPSTASH_REDIS_TOKEN - Upstash Redis token (optional)

Command Options

# Scan a specific directory
spectra init /path/to/project

# Use a custom API URL
spectra init --api-url https://custom-api.example.com/

# Check version
spectra version

Local Development

Running the API Locally

1. Install API dependencies:

   pip install -r api/requirements.txt
   

2. Set OpenRouter API key:

   export OPENROUTER_API_KEY='your-openrouter-api-key-here'
   

   Get your free API key from https://openrouter.ai/keys (no credit card required)

3. Run the API server:

   uvicorn api.index:app --host 127.0.0.1 --port 8000
   

4. Test the CLI:

   export SPECTRA_API_URL='http://127.0.0.1:8000/'
   spectra init
   

Deployment

Deploy API to Vercel

1. Install Vercel CLI:

   npm install -g vercel
   

2. Login to Vercel:

   vercel login
   

3. Deploy:

   vercel deploy
   

4. Set environment variables:

   vercel env add OPENROUTER_API_KEY
   # Paste your OpenRouter API key when prompted
   # Get free key from https://openrouter.ai/keys
   

5. Redeploy to apply changes:

   vercel --prod
   

6. Update CLI to use production API:

   export SPECTRA_API_URL='https://your-api.vercel.app/'
   

Project Structure

spectra-cli/
├── spectra/              # CLI package
│   ├── __init__.py
│   ├── main.py          # CLI entry point
│   ├── scanner.py       # Project scanner
│   └── client.py        # API client
├── api/                 # Serverless API
│   ├── index.py        # FastAPI app
│   └── requirements.txt
├── requirements.txt     # CLI dependencies
├── pyproject.toml      # Package configuration
├── vercel.json         # Vercel config
└── README.md

Supported Tech Stacks

• Node.js - Detected via package.json
• Python - Detected via requirements.txt, Pipfile, or pyproject.toml
• Java (Maven) - Detected via pom.xml
• Java (Gradle) - Detected via build.gradle
• Go - Detected via go.mod
• Rust - Detected via Cargo.toml
• PHP - Detected via composer.json

Requirements

• Python 3.8 or higher
• OpenRouter API key (for the API server) - Get free key from https://openrouter.ai/keys
• Internet connection (to call the API)
• Upstash Redis (optional, for production job queue)

Troubleshooting

CLI can't connect to API

• Check that SPECTRA_API_URL is set correctly
• Verify the API server is running (if testing locally)
• Check your network connection

No files generated

• Ensure your project contains recognizable files (package.json, requirements.txt, etc.)
• Check that the API is responding correctly
• Review API logs for errors

API errors

• Verify OPENROUTER_API_KEY is set correctly on the server
• Get your free API key from https://openrouter.ai/keys (no credit card required)
• Check OpenRouter API status at https://openrouter.ai/status
• For job queue issues, verify UPSTASH_REDIS_URL and UPSTASH_REDIS_TOKEN are set (optional)
• See API_V2_DOCS.md for troubleshooting

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License - see LICENSE file for details

Support

For issues and questions:

• Open an issue on GitHub
• Check the documentation
• Review the troubleshooting section

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Built with ❤️ by the Spectra team